Tech Lead – Software Engineering

🔥 5 minutes ago

🇮🇪 Ireland – Remote

💵 €90k - €120k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 5%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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DataVisor

WebsiteLinkedInAll Job Openings

51 - 200 employees

💸 Finance

💳 Fintech

☁️ SaaS

💰 Series C on 2019-10

Finance • Fintech • SaaS

DataVisor is an advanced fraud and risk management platform leveraging AI and machine learning to provide real-time solutions for financial institutions and other large organizations. The platform offers a comprehensive suite of tools to tackle various types of fraud, including account takeovers, application fraud, ACH and wire fraud, card fraud, and check fraud. DataVisor also provides solutions for AML (Anti-Money Laundering) compliance, helping banks, credit unions, fintech companies, and digital payment services detect and prevent fraudulent activity. Through its innovative machine learning algorithms and real-time data orchestration, DataVisor allows organizations to streamline their operations, reduce fraud losses, increase approval rates, and maintain compliance, all while protecting the integrity of their systems and user data. The company emphasizes quick and efficient integration with existing systems and provides educational resources to stay ahead of emerging threats, making it a valuable partner for modern financial operations.

📋 Description

• Own the technical direction of the real-time detection platform, including streaming, storage, and the training pipelines that support it • Translate product and engineering roadmaps into clear technical plans, milestones, and execution priorities • Proactively identify technical risks, dependencies, and trade-offs before they impact delivery • Lead design and architecture reviews, make technical trade-off decisions, and document the reasoning behind key decisions • Stay hands-on by coding, reviewing code, debugging issues, and supporting the team during production incidents • Mentor engineers and raise the bar for system design, code quality, operational excellence, and technical execution • Own the operational health of the platform, including alert quality, on-call load, incident follow-through, and root-cause prevention • Partner directly with Product, TAM, and customer-facing teams on customer-impacting issues, ensuring clear impact assessment, prioritization, ownership, and next steps • Define how the team uses AI agents and AI-assisted tools in engineering workflows, including verification standards and safe usage practices • Build, evaluate, and improve LLM- and agent-assisted tools for engineering and operations use cases, such as triage, root-cause analysis, alert summarization, and evaluation harnesses

🎯 Requirements

• 8+ years of software development experience • 2+ years of technical leadership experience as a tech lead, staff engineer, engineering manager, or similar role • Proven ability to lead technical outcomes across a team, including work you did not personally implement • Deep production experience with Java, along with working proficiency in Python and Shell scripting • Experience designing, building, shipping, and operating distributed real-time systems at scale • Strong knowledge of computer systems, relational databases, and SQL • Experience building and optimizing multithreaded and concurrent applications • Hands-on experience with Cassandra, Yugabyte, Flink, Spark, or Kafka • Experience with the Spring Framework • Demonstrated use of AI coding tools such as Claude Code, Cursor, GitHub Copilot, or similar tools in real production work • Ability to set team-level standards for AI-assisted engineering, including how tools are used, how outputs are verified, and when AI-generated suggestions should be rejected • Strong verification discipline, with the ability to validate model outputs against source code, logs, documentation, and production behavior • Bachelor’s degree in Computer Science or a related field is required • EU Citizen or Ireland PR is required • Experience in fraud, risk, payments, financial services, or another domain where false negatives carry significant business or customer impact • Experience owning ML platforms or large-scale training pipelines • Experience with Kubernetes • Experience building with LLM APIs, agent frameworks, tool calling, RAG, or MCP • Experience writing evaluations or regression tests for non-deterministic systems • Experience hiring, managing, or mentoring engineers • Experience with test-driven development

🏖️ Benefits

• Health insurance • PTO • Equity